Abstract
This paper aims to provide a comprehensive survey of recent advancements in modelling and autonomous manipulation of non-rigid objects. It first summarizes the recent advances in sensing and modelling of such objects with a focus on describing the methods and technologies used to measure their shape and estimate their material and physical properties. Formal representations considered to predict the deformation resulting from manipulation of non-rigid objects are then investigated. The third part provides a survey of planning and control strategies exploited to operate dexterous robotic systems while performing various tasks on objects made of different non-rigid materials.
Highlights
In order for robots to reach the milestone in task flexibility and come closer to a human-like skillset, an important task that remains largely unsolved is the proper handling of non-rigid objects.This includes any object that can change shape while being manipulated, such as rope, wires, metal plates, fabrics, sponges, rubber, organs and living tissues, etc
A very recent review by Sanchez et al [3] provides a broad coverage of the topic, focusing on the classification of control tasks based on the type of object being handled as well as on the specific subtask that is performed in the various steps of manipulation and shape control
This paper presents a review of the latest developments related to the robotic manipulation of non-rigid objects, providing a symbiotic coverage of the sensing, modelling and control strategies used in these systems
Summary
In order for robots to reach the milestone in task flexibility and come closer to a human-like skillset, an important task that remains largely unsolved is the proper handling of non-rigid objects. This organization of topics does not aim to build a formal and systematic classification of objects and tasks as it was done in [3], but rather to group similar research in order to let the trends emerge naturally. It is sensible to decouple sensing, modelling and control by organizing models and sensing technologies based on their characteristics while control strategies are grouped based on the task to which they are applied This promotes a clear logical separation between the core components of any robotic system, i.e. sensing, modelling and control, which makes for a perspective that complements previous reviews and provides support for those who may be interested in a specific component of such a system
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